Long-term efficacy of a rural community-based integrated intervention for prevention and management of chronic obstructive pulmonary disease: a cluster randomized controlled trial in China's rural areas

This study aimed to assess the efficacy of a rural community-based integrated intervention for early prevention and management of chronic obstructive pulmonary disease (COPD) in China. This 18-year cluster-randomized controlled trial encompassing 15 villages included 1008 patients (454 men and 40 women in the intervention group [mean age, 54 ± 10 years]; 482 men and 32 women in the control group [mean age, 53 ± 10 years]) with confirmed COPD or at risk for COPD. Villages were randomly assigned to the intervention or the control group, and study participants residing within the villages received treatment accordingly. Intervention group patients took part in a program that included systematic health education, smoking cessation counseling, and education on management of COPD. Control group patients received usual care. The groups were compared after 18 years regarding the incidence of COPD, decline in lung function, and mortality of COPD. COPD incidence was lower in the intervention group than in the control group (10% vs 16%, <0.05). A decline in lung function was also significantly delayed in the intervention group compared to the control group of COPD and high-risk patients. The intervention group showed significant improvement in smoking cessation compared with the control group, and smokers in the intervention group had lower smoking indices than in the control group (350 vs 450, <0.05). The intervention group also had a significantly lower cumulative COPD-related death rate than the control group (37% vs 47%, <0.05). A rural community-based integrated intervention is effective in reducing the incidence of COPD among those at risk, delaying a decline in lung function in COPD patients and those at risk, and reducing mortality of COPD.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively.

Prevalence of untreated caries in deciduous teeth in urban and rural areas in the state of Sao Paulo, Brazil

Objectives. To describe the prevalence of dental caries in children with deciduous teeth in urban and rural areas in the state of Sao Paulo, Brazil, and to identify associated factors. Methods. The study included 24 744 children ( 5 - 7 years of age) examined as part of an epidemiological survey on oral health carried out in the state of Sao Paulo ( Levan-tamento Epidemiologico de Sa de Bucal do Estado de Sao Paulo). Multilevel analysis was used to investigate whether the prevalence of untreated caries was associated with the sociodemographic characteristics of the children examined or with the socioeconomic aspects of the participating cities. Results. Being black or brown ( adjusted odds ratio ( OR) = 1.27), attending school in rural areas ( adjusted OR = 1.88), and attending public school ( adjusted OR = 3.41) were identified as determinants for an increased probability of presenting deciduous teeth with untreated caries. Being a female ( adjusted OR = 0.83) was identified as a protective factor. The negative coefficients obtained for second- level independent variables indicate that the oral health profile of the cities included in the study were positively impacted by a higher municipal human development index ( beta = - 0.47) and fluoridated drinking water ( beta = - 0.32). Conclusions. The prevalence of untreated caries is influenced by individual and sociodemographic factors. The present study provides epidemiological information concerning the rural areas in the state of Sao Paulo. This information is useful for strategic planning and for establishing guidelines for oral health actions in local health systems, thereby contributing to oral health equity.

Global and diffuse solar irradiances in urban and rural areas in southeast Brazil

The seasonal evolution of daily and hourly values of global and diffuse solar radiation at the surface are compared for the cities of Sao Paulo and Botucatu, both located in Southeast Brazil and representative of urban and rural areas, respectively. The comparisons are based on measurements of global and diffuse solar irradiance carried out at the surface during a six year simultaneous period in these two cities. Despite the similar latitude and altitude, the seasonal evolution of daily values indicate that Sao Paulo receives, during clear sky days, 7.8% less global irradiance in August and 5.1% less in June than Botucatu. On the other hand, Sao Paulo receives, during clear sky days, 3.6% more diffuse irradiance in August and 15.6% more in June than Botucatu. The seasonal variation of the diurnal cycle confirms these differences and indicates that they are more pronounced during the afternoon. The regional differences are related to the distance from the Atlantic Ocean, systematic penetration of the sea breeze and daytime evolution of the particulate matter in Sao Paulo. An important mechanism controlling the spatial distribution of solar radiation, on a regional scale, is the sea breeze penetration in Sao Paulo, bringing moisture and maritime aerosol that in turn further increases the solar radiation scattering due to pollution and further reduces the intensity of the direct component of solar radiation at the surface. Surprisingly, under clear sky conditions the atmospheric attenuation of solar radiation in Botucatu during winter - the biomass burning period due to the sugar cane harvest - is equivalent to that at Sao Paulo City, indicating that the contamination during sugar cane harvest in Southeast Brazil has a large impact in the solar radiation field at the surface.

Methodological issues in applying Location Models to Rural areas

Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.